End-to-End Speech Recognition from Federated Acoustic Models
Author:
Affiliation:
1. University of Cambridge
2. Avignon University
3. Telecom Paris
4. University of Oxford
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9745891/9746004/09747161.pdf?arnumber=9747161
Reference36 articles.
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2. Importance of Smoothness Induced by Optimizers in Fl4Asr: Towards Understanding Federated Learning for End-To-End ASR;2023 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU);2023-12-16
3. Toward a Personalized Clustered Federated Learning: A Speech Recognition Case Study;IEEE Internet of Things Journal;2023-11-01
4. Learning domain-heterogeneous speaker recognition systems with personalized continual federated learning;EURASIP Journal on Audio, Speech, and Music Processing;2023-09-05
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